“Let me tell you a wonderful old joke from communist times. A guy was sent from East Germany to work in Siberia. He knew his mail would be read by censors. So he told his friends: Let’s establish a code. If the letter you get from me is written in blue ink, it is true what I said. If it is written in red ink, it is false. After a month his friends get a first letter. Everything is in blue. It says, this letter: everything is wonderful here. Stores are full of good food. Movie theaters show good films from the West. Apartments are large and luxurious. The only thing you cannot buy is red ink.”

Great joke. No doubt scrutinizing your trading data to make sense of it is like something written in red, the code for which is blue.

Speaking of which, chances are, your earnings date is approaching. Your intraday volatility (spreads between high and low prices) is perhaps 4%. Across our client base, it’s now over 4% on average. To help you make sense of your stock price, the exchanges and designated market makers and surveillance firms are giving you columns of data on trading by different brokers and sector or economic news. They tell you so-and-so upgraded the sector, causing a strong rally.

You’re not sure. In your gut you think the euro has got a lot to do with it. Maybe the dollar. It would be nice to know. And it would help if you could assess how money will react to the news you announce next week or the week after.

There’s a lot you can know (don’t miss the Nov 3 IR Magazine Think Tank where we’ll discuss it). As much as we rant about the Swiss-cheese state of data for issuers in a gold-bar kind of world for speculators, your trading data in context of market rules is like an electrocardiogram. You can identify what generates the pulse and what’s driving fear and greed in the corpus of your equity market.

It’s a math problem (oh boy). I randomly sampled ten market structure reports for clients. In the past five trading days, Rational share of volume ranged from 10% to 16%, with an average of 12%. Speculative trading averaged 34%; Programs reflecting passive behavior were 29%. Another 24% went to risk-hedging and other things that don’t fit these buckets.

So if you are going to beat your active investors’ expectations on the call, and they consequently value your shares 5% higher, but programs for funds and models – asset managers – set your value 3% lower because of balance-sheet issues, what might happen to your stock?

It’s math. Programs are 29% of your market, so their pricing weight is twice the factor of rational investment. And if speculators have multi-leg straddles that pay off in cash if your shares move down, we can run a calculation that projects what will happen.

We are almost always within 1%. So we must be doing something right. If your stock were trading at $36 ahead of your call, we’d project a close at $34.81, with these expectations applied to outcomes.

How can this be? Markets are a maze of varying purposes and horizons following prescribed rules and order-types to match up as buyers and sellers. This mathematical maze can be sorted through a model.

Since rational investment is about 12% of the market, using data analytics to understand your trading – the same things the folks do who trade it to begin – is a good idea for the IR chair today. You know the 12%. You talk to them all the time. It’s the rest you need to get a grip on, so you can equip management with rational expectations.

We are willing to bet the sum total of wages for a large Wall Street demonstration that no surveillance firm or exchange can equip you with these answers.

We were there, clanging bells and hooting our hearts out. Here is winner Levi Leipheimer readying for the time trial that put him in yellow. The peloton left Avon here for Steamboat, and Levi is visible midway in yellow. At the finish, some 250,000 jammed downtown Denver for the epic, lapping conclusion. We are proud of American cycling and our state’s awesome organizational effort.

Speaking of peloton, Wall Street Journal reporter John Jannarone wrote Monday in the Heard column called “Traders Seek Salvation from Correlation” about how stocks race in formation. It’s among the best pieces we’ve seen on modern trading. Jannarone says that S&P 500 stocks show 80% correlation in the past month, meaning eight in ten move synchronously.

This is a source of distress for IR folks trying to distinguish a strong company story from the herd. We’d argue that rather than slamming the collective IR noggin into the burgeoning brick wall of macro-focus investing that you instead track program trading and establish what level is acceptable – and use it as an IR success measure. We wrote about this last week, so we won’t retrace the trodden path.

Why a mirror image across so much of the market? One driver Jannarone posits is Exchange-Traded Fund investing. According to Credit Suisse, these drive some 30% of daily stock volume. Jannarone also notes that trading in S&P 500 E-mini futures contracts is more than four times the combined daily volume of the two biggest S&P 500 ETFs, the SPDR, and iShares S&P 500 Index ETF.

It’s a reasonable hypothesis. If institutions trade ETFs and indexes, and hedge them with futures and options, and try to increase yield by leveraging assets with yet more futures or options in, say, currencies and Treasuries, stocks will correlate in models, and markets will reflect high volatility due to continual adjustments to these layers of equities and derivatives.

We see it, measuring speculative and program-driven trading for clients. These two dominating behaviors are also increasingly correlated. More money is pursing short-term “investment” horizons designed to produce returns in days.

Jannarone worries as do many investors that correlation is likely to last because of currency concerns. We agree. So IR should quantify market activity and report on it regularly to management. Otherwise, we’re bystanders. It’s better turning lemons to lemonade than sourly wondering when rational investment will return.

We suggest you hop on that bike and ride it.

The dollar dropped for a second straight day today. Stocks are again up, like they were yesterday. The dollar gained ground last Wed-Fri, and stocks fell.

This week marks the end of the month and quarter. We recommend in our IR Calendar that you consider some tactical timing as part of your overall IR strategy. Generally, the last few trading days of a quarter or month aren’t best for releasing good news. But they may be perfect for bad news.

Why? Institutions will be shoring up portfolio returns or managing exposure to market risk. They address risk by offsetting it with something that is inversely correlated. Notice that stocks and the dollar are inversely correlated. Notice that the dollar and other currencies, such as the Euro, are often inversely correlated.

All institutions try to generate yield from assets – managed money – through short-term trading. That’s what we’re seeing now. Money is trying to make up for a lackluster month through aggressive short-term trading. Is that investment? Only if you think any form of buying low and selling high, even in 30 microseconds, is investment. We call that speculation.

Back to macro behavior, markets execute transactions in currencies that are valued relative to other currencies today rather than fixed according to income or net worth of countries. Suppose the value of your house were tied to the value of houses in Greece. In a sense, it is, because the value of the currency in your pocket varies according to the one used in Greece, the Euro.

Now, think about all of these things from an investment standpoint. If the value of your house was a big part of your balance sheet – true for most of us – but it varied according to factors that had little to do with the supply or demand for houses of a kind and location like yours, or the particular distinguishing features of your house, would you be more or less inclined to buy a house?

You’d probably be less likely, right? Now translate these analogies to your IR program and the ends of months and quarters. Our measures show that some 85% of all daily volume is a form of short-term trading for yield, or risk-management activity to balance out exposure across many assets, not just stocks. Investors set the prices of stocks in our client base 20-30 times per year on average, while market prices are changing every day.

Investors are least likely to set prices at the ends of months and quarters, and during options expirations. There are bigger priorities, and 85% of money is moving en masse or chasing minute divergences. It’s not focused on investing in the neighborhood, so to speak.

Suppose you announced good news today. Your stock briefly separates from peers and the market – most times speculators are responsible. In the next two days it’s equalized by macro factors affecting large baskets of securities. This is your house getting valued with Greece, so to speak.

Conversely, if you put out bad news in the last three days of a month or quarter, traders and risk managers might buy your stock the following day or two anyway, simply because it temporarily diverged and now offers hedge or yield characteristics. Plus, who wants to sell a stock and hurt portfolio performance on the last trading day?

In new months, you have a better chance to stand out from the crowd. Why? Stock pickers have a long time to be rewarded – a full month!

These are realities in markets driven by machines and relative value. Turn them to your advantage wherever possible, by understanding them.

Today is the anniversary of Pearl Harbor. Near the end of WWII, my great uncle, Jack, was one of 316 sailors from 1,200 aboard the USS Indianapolis to survive its sinking and days in shark-ridden waters in the south pacific. Tough fellows, those guys.

On that happy note, let’s turn to everybody’s favorite topic: math. Click here for an example of math in action, a chart showing the spot market for the US dollar, called the DXY, and the Dow Jones Industrial Average, the past three months. The two juxtapose like the mirror image of a mountain in a still lake on a clear day. Wherever one goes, the other is equally opposite.

IR pros, this should hearten those of you wandering the Wilderness of Answers About Trading. Why? If math is so measurable in one place, it’s equally measurable in others. Measures are answers.

I traded notes with the IRO for a megacap – obviously not a client – who lamented, “There are no answers.”

To quote the French, “Au contraire.” Answers abound. And we have math to thank for that. All trades must meet at the National Best Bid or Offer. That’s a math equation. All broker-dealers must hew to rules on reporting trades and meeting best execution standards. More math. Algorithms, which are math equations, drive, oh, call it 98% of equity volume. The entire US trading environment is predicated on technology and rules built around math.

What’s unpredictable is human behavior. Try tracking a schizophrenic (no offense to any schizophrenics). Now that’s challenging. But math? It’s just equations. This is also why speculative traders look gleefully at today’s markets and rub their digits together, little zeroes and ones full of anticipation.

But we can see them getting excited, just as they did Dec 3. Across the markets Dec 3 came a rush of speculative excitement. Perhaps it related first and foremost to the math we noted above – expected weakening of the US dollar (on ebbing Euro fears and the Germans readying to sacrifice more of Deutschland to the greater, weaker good) and its correspondent boost in US equities. Whatever the case, speculation is driving stocks, and we can see it.

If we can see it, so can you, and even more specific things. Say for instance, how program trading changes in this particular stock in the technology group, or how thoughtful investment dollars, differing from macro trades around, reflect value-buying in an office REIT. Or how month-end moves by quantitative institutions in a small-cap technology stock, evident in a big lump of volume in a predictable place and smatterings elsewhere, attracted value buyers, thus also revealing the stock’s rational price (where thoughtful investment dollars compete with other behaviors).

IROs, there is a place for math in your program. It should be simple. We recommend basic weekly “market structure” (behaviors behind price and volume) measures. Quantify crowd behaviors with program trades. Speculation through tracking volatility executions. Rational activity by observing some firms who execute trades but can’t speculate well or run big programs (the lack of this latter illustrates how widely math has been embraced in trading markets).

We’ve already figured out how to do it. If you want to do it yourself, as I used to do in the IR chair, look at your trading activity. It need not be perfect. The same mathematical rules apply across the National Market System. Start measuring the data in comparison to what you say or do, and when you say or do nothing. Compare.

Yes, math is a four-letter word. But so is love. And maybe the IR profession needs to love some math, and stop looking for love in all the wrong, old places.

It’s a decent name for a rock band, yes. But it means “what stuff can you do with this?”

Traders want actionable data – something to drive opportunity for profit. Investor-relations professionals want actionable tools – something that’ll improve stock ownership, share price, results of IR effort.

Knowing who owns your stock is good. But what actions can you take? Talk to sellers? That’s uncomfortable. Plus, unless you’re screwing up, selling is a compliment, an investment objective. The sellers should well buy again, when the time’s right.

How do you know the time’s right? Ownership and targeting data are fine but limited if you don’t know who or what is controlling your liquidity. Without knowing your trading behavior, it’s difficult to accurately measure actions, plot outreach, and target investors.

Money won’t simply take a flyer because you run a good business and your IR team is suave and debonair. Today, institutions cannot afford to buy stocks in a vacuum, without respect to how the first 1,000 shares alter baskets, ETFs, derivative trading tactics and all the rest swirling around your liquidity. Institutions mind risk-management obsessively now, which is about market structure.

We track data for a living. For clients, we graph volume from prop traders like RGM Advisors, against, say, executed order flow for Credit Suisse. We observe how the behaviors of the two are eerily similar in some issues (and not in others). RGM is a scientific, machine-learning trader.

Say you’re using Credit Suisse for support on a non-deal road show, but most of their volume is trend-driven. That knowledge should inform what investors you ask Credit Suisse to bring from its client ranks. You’ll want high-turnover GARP or growth money, because that’s the kind likely to wade into a mathematical market. It can be a win-win – Credit Suisse likes those customers, too.

Market structure can shape who you choose for support. Some firms have high-turnover clients because their trading products facilitate high-speed trading. If you’re after a different investor-class than what a sellside firm tends to serve, you might use a different firm with a lesser trading operation – and thus more dependence on its research. Great story isn’t enough. If your market structure doesn’t suit the money you’re targeting, you’ll waste a road trip.

IR professionals should become more tactical. Use the big picture to do it – beyond story, to structure. The final frontier for IR effectiveness rests on the actionable quality of market-structure data. Do you know how much of your daily volume is speculation? What kind of investor should you target tactically, in context of your IR strategy, if more than 50% of your volume is arbitrage? These are important things to know now.

Here’s a product announcement from Direct Edge yesterday:

ACK – SPX Accelerated Return Notes due September 30, 2011

CDK – SPX Capped Leveraged Index Return Note due July 27, 2010

ELD – WisdomTree Emerging Markets Local Debt Fund

MHM – SPX Market Index Target Term Securities due July 31, 2015

As products like these roll out each day, there’s something else for that money you’re meeting in Chicago to choose besides you. Kick it up a notch. Target more tactically. Sometimes you’re right for high-turnover hedge funds. That alone is a new notion. Then, be ready, using market structure as guide, to get on the radar of conventional fund investors before hedge funds rotate.

It’s not an exact science. But these are tools with abundant actions. If you’re expert in your own market structure, your results are going to be different from those of other IROs, because you’ll think differently about what actions you need to take.

You’ll be the IRO for the 21st century.

That’s the essence of conversations I had yesterday with two investor-relations officers. It’s tempting to suggest asking Al Gore about why things that should be up are instead down. But that’s an old joke. And it won’t make you more valuable in the IR chair.

What will enhance your value is knowing what to tell the CFO and how best to do it. Whether you provide a daily, weekly or quarterly update to management about factors behind your stock price, you should incorporate comments on your market structure. Not just the old conventional stuff.

Think of market structure this way. If you operated a retail store, and each week you summarized the state of things in your store for headquarters, you’d talk about financial performance, products moving off shelves, the traffic driving sales, and trends. Something like that, anyway.

Same with your stock’s “market structure.” There’s only one product, your shares. But otherwise, you’re assessing behaviors and measuring them to understand how your store serves its market. If you measure only one behavior or one group of customers, that’s not an accurate picture of what’s happening, and it’s bound to lead to head-scratching and questions like, “How come our stock is down when it should be up?”

What do you tell your management team about market structure? Well, say you’re providing a weekly brief on trading activity. First define your metrics – the things you’ll track. For a weekly report, you don’t want to bury them in mind-numbing data. You want a small set of consistent measures. Begin with things like the percentage premium or discount in your closing price for the week versus the trailing 20-day average price. Volume versus 20-day average. Daily average trades and shares per trade, and daily dollar flow – that is, average daily price multiplied by average daily volume.

In time, you can provide a forward-looking expectation from data – but you must accumulate metrics first. As your management team becomes accustomed to market structure information, move to simpler but more compelling information, derived from your data: What’s setting our price? What do investors think? What are traders and risk managers doing, as opposed to what investors think? What’s likely to happen to our price next? These conclusions are extrapolated from data.

Before you know it, you’ll own your market structure. You’ll be the expert on matters related to your trading. This is the first step in a larger process of making a home for market structure in the IR department just like corporate governance has become an IR bailiwick.

Why must you own your market structure? Because roughly 90% of volume today BEHAVES either according to market risk or in response to speculative opportunity, and only a small amount is rational, or seeking long-term returns. If IR spends 90% of its effort on 10% of the market, well, at least something should be known about the rest. Or else, how can you draw accurate conclusions about stock performance, or even investor sentiment?

It’s up to IR to set that agenda and drag management kicking and screaming into the 21st century of how trading markets work.

To conclude, a challenge for you IR readers: Look up the DXY – the dollar index futures contract – and compare it to the Dow Jones Industrial Average, over, say, the past year, or the three months around the May 6 Flash Crash. What does it show you?

Everybody’s got an opinion on why the market is yinning and yanging. We, I believe uniquely in IR, look at market structure first. That is, we see the trading data and behavior, and then from it we ask, “Why did that happen?”

Most everybody looks at what happens and infers that these are the causes for market activity. But, here’s the thing: money moves for three reasons today – investment behavior, speculation, and risk-management. It’s easy to get it wrong from the outside looking in. Thus, we think there’s greater accuracy in drawing conclusions from the evidence than in applying the evidence to your conclusion.

We saw a large rift form in the equity markets on February 2. Trading and investing activities were subordinated to risk-management flows. These are orders managed by software systems that respond to instructions and data about market risk. It may have been prompted by Greece’s problems. Perhaps American jobs data, or central bank woes in Argentina, where inflation was 17% in 2009. Maybe something else.

But that would be looking in from the outside. Inside looking out, here’s what happened: Systems executing orders for defensive reasons rose up in mass. It’s like a crack in the continental crust that squeezes out the stuff that forms mountains. Except here, it was risk-management volume – both buying and selling – that extruded from the rupture. When it ripples through nearly every issue like a fault line, you may be fairly certain it’s macroeconomic, not about your stock or story.

In fact, from the completion of monthly expirations on Jan 20, to February 4, we saw strong indications of risk management trading. It was similar to what we observed on October 1-2 last year, when the markets nearly fractured, and akin to the “healing” volumes in March and April 2009.

There are certain entry points where these volumes can be found. Among them is Goldman Sachs. When GS appears with large volume increases in 80% of issues (but you won’t see it in trading volumes), it’s a curious thing, and it affects all other behaviors. If you try to isolate whether it’s buying or selling, it’s impossible. All programs do both. So it requires seeing the activity in relation to other activities in order to understand what form of behavior has changed conditions in the markets.

Goldman isn’t alone. In fact, most times these volumes hit the markets through “sponsored access,” one of the activities that the SEC considers a gateway for exploitation. We don’t know if that’s true or not. We do know that in three different significant instances in the past twelve months, sponsored access has helped the markets heal.

We call these events “synthetic weaves” in the markets, stitching up a gash in the market structure. It leaves big question marks. Who’s behind it? Where is the money coming from? Why does it buy and sell seemingly unrelated issues en masse? Is it helpful or hiding a chasm ahead?

We can posit ideas in response, but who’s to say? We surmise, however, that economic data are secondary to the supply and pricing of currencies. And we can think of only one force with that sort capital capability.

Why does it matter? It’s a great way to clear the crowd out from around the water cooler. People quickly go quiet and start glancing at their watches when you let drop “synthetic weave in the equity markets.” Also, it helps explain why your business isn’t properly valued by trading markets.

Speaking of chaotic action, let’s review trading basics. We tend to think trading is buying and selling stock. To quote John Kerry, would that it were! Most trading today isn’t done for capital appreciation but to capture short-term divergence or to balance risk.

We’ll start with the big picture. The broad market-structure profile thus far in January isn’t too different from the same period in December, except volumes are up about 20%. The increase is mostly electronic market-making – think of it like transaction processors who don’t own things but simply facilitate commerce for a fee. By our measure, that’s about 36% of trading.

Who’s doing business with them? For one, speculators. These participants, which range from the largest bulge-bracket desks to the smallest introducing brokers, have driven about 33% of volume in January. Notice that it’s similar in size to the EMM segment.

Risk-management program-trading is another roughly 21%. This activity rebalances index vehicles, mutual funds, asset-allocation models, counterparty obligations and so on. The remaining 10% is active investment. There’s some crossover of course, because algorithms run close to 98% of volume today and barely any trades are old-fashioned manual entry.

Keep in mind that investors pursuing value and growth don’t trade every day. They tend to do thing in lumps and globs. Still, owning things for sustained periods is risky business now. Instead, securities are in constant motion. This is why speculative and market-making volumes are so high. Inexpensive, high-speed execution is ubiquitous because there is constant, chaotic motion of shares, driven by complex mathematical systems.

Even active money moves this way. What an investor thought yesterday about the value of a given stock may be different today. Perhaps program trading changed, causing sales traders and execution specialists to take offensive or defensive postures. There’s no stasis in the markets, unless it’s what regulators illogically and weirdly hope to achieve with “systemic risk.”

Ironically, these conditions mean market structure is easier to understand than you might think. Math is logical. Even Chaos Theory is a mathematical proposition. Things move from a state of order to a state of disorder. Molecules move apart over time to fill available space.

This matters, IROs, mostly because it’s reality. We can deny reality and continue to do the same old thing. Or we can be proactive and redefine our job and its measures.

Resolve that Twenty Ten is the year you’ll get to know your market structure and introduce your management team to your stock’s Market Structure Profile.

I grew up in the Snake River Breaks northwest of Boise. In tiny Huntington, where I quarterbacked the eight-man high-school football team, a guy ahead of me several years achieved local fame at middle linebacker for the Boise State Broncos. BSU was I-AA back then, in the Big Sky league. Last night, it was great seeing the Broncos go 14-0, beating undefeated and 4th-ranked TCU in the Fiesta Bowl. The little big sky school has come a long way.

Speaking of a long way, here we are in Twenty Ten. What to expect this year? Lots of fun, of course! For those of us hovering about the gilded IR chair, it’ll be the year you create job security for yourself by knowing your market structure. The moment you start chattering about risk-management resets, you might see the eyes of execs glazing over – but they’ll be happy to pay you to know what you’re talking about! I’d say that’s worth looking forward to.

And will we here at The Map shut up about money supply already? Nope. You’ll hear more about monetary policy, because it’s the entire – yes entire – reason that neither the IR industry nor the global economy is really, in fact, growing. You cannot claim to have a free market and at the same time manage market outcomes with monetary policy. Nobody knows the value of things, then, and that’s really bad if you’re trying to create value.

Plus, Nature constantly changes. Capitalism is profitable adaptation to change. When the whole world is fixated on keeping some unfortunate event from ever happening again – trying to stop change – we are defying not only Nature, but the very thing that fosters prosperity and a vibrant IR profession – adapting to change.

As to what happens in the markets, nobody can predict the future. Money will continue to value your stock on the basis of use, with risk managers more powerful, investors less powerful, and speculators reacting to both. We track the behavior of money because IR folks now must be purveyors of knowledge, not just voices to investors. Knowing what’s happening, even if you can’t change it, is critical to IR value.

Differing ways money uses stocks is likely to result in continued broad equity appreciation, perhaps beyond 11,000 on the Dow. But like a bungee cord, markets stretched by elastic money supplies will contract. Period. Equity markets do still reflect the value of created things. Even if risk managers continuously tweak settings and speculators arbitrage movements. If we’re not creating things, and we’re gumming the gears of adaptive change with rules and hoops and do’s and don’ts in a bid to protect ourselves from the scary unknown, our equity markets will come to reflect moribund inertia.

Moribund Inertia isn’t even a good name for a rock band. So let’s change it.

As I move the midsection flab from a grand Thanksgiving holiday aside to get at the keyboard (a little humor there), the US equity markets are closing up again. IR folks and executives, what’s proving the most accurate indicator of market direction lately? And what’s it mean to your own market structure?

“Market structure” is your trading environment – what’s setting share price and driving trading volume. In business, there are metrics of health ranging from EPS, to cash-flow ratios, to margins, to operating statistics like subscribers, or phone lines, or manufacturing capacity, or load rates.

The same is true for market structure, except the metrics aren’t financial or operational, but measures of speculation, investment and risk management. Tracking the effects of these forces offers a highly accurate picture of the health of your market structure. As you long-time readers know, we believe market structure measures are fundamental now, the same as MRIs for medical diagnostics or satellite images before sending troops into battle.

Back to our question above, about the most accurate indicator of market direction, have you got your answer in mind? Okay, it’s this: the dollar. Go run a graph. For at least a couple months now, US equities move with inverse correlation to the dollar. When it falls, stocks strengthen. When it rises, stocks drop. Now, why would that be?

As you ponder that, consider this too. Trading data show a steady if subtle migration of volume – lighter now than in the summer – to pure quantitative multi-asset-class systems. It makes sense to us. If financial securities modulate according to US currency, which ripples through various asset classes from bonds, to commodities, to fixed income securities, and then alpha forms between global markets, why wouldn’t you trade on high-speed data rather than financial measures? It’s, as Sherlock Holmes would say, elementary, my dear Watson.

Thus, institutions shift their focus further from business fundamentals to instances of speculation and risk-management. Profits come from brief divergences in asset classes. It becomes a foot race for trading systems. If the dollar strengthens and US stocks fall, where will they rise fastest and where do you trade puts and calls? Probably Asia. And maybe you trade some corporate bonds and some US futures too, knowing the dollar will fall again, positively impacting these asset classes.

Do you see the problem? You will be rewarded less for running a great business. We return to this issue because it’s the heart and soul of our profession. We are the marketing and communications function for the world’s great long-term investments. Let’s fight for markets that reward effort rather than foot speed in very short sprints.

So why does a weak dollar reward stock prices? Give us your thoughts!